Evaluation of Parallel Paradigms on Anisotropic Nonlinear Diffusion

  • S. Tabik
  • E. M. Garzón
  • I. García
  • J. J. Fernández
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4128)


Anisotropic Nonlinear Diffusion (AND) is a powerful noise reduction technique in the field of computer vision. This method is based on a Partial Differential Equation (PDE) tightly coupled with a massive set of eigensystems. Denoising large 3D images in biomedicine and structural cellular biology by AND is extremely expensive from a computational point of view, and the requirements may become so huge that parallel computing turns out to be essential. This work addresses the parallel implementation of AND. The parallelization is carried out by means of three paradigms: (1) Shared address space paradigm, (2) Message passing paradigm, and (3) Hybrid paradigm. The three parallel approaches have been evaluated on two parallel platforms: (1) a DSM (Distributed Shared Memory) platform based on cc-NUMA memory access and (2) a cluster of Symmetric biprocessors. An analysis of the performance of the three strategies has been accomplished to determine which is the most suitable paradigm for each platform.


Message Passing Structure Tensor Distribute Shared Memory Hybrid Code Parallel Paradigm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Weickert, J.: Anisotropic Diffusion in Image Processing. Teubner (1998)Google Scholar
  2. 2.
    Perona, P., Malik, J.: Scale space and edge detection using anisotropic diffusion. IEEE Trans. Patt. Anal. Mach. Intel. 12, 629–639 (1990)CrossRefGoogle Scholar
  3. 3.
    Weickert, J.: Coherence-enhancing diffusion filtering. Int. J. Computer Vision 31, 111–127 (1999)CrossRefGoogle Scholar
  4. 4.
    Weickert, J.: Coherence-enhancing diffusion of colour images. Image and Vision Computing 17, 201–212 (1999)CrossRefGoogle Scholar
  5. 5.
    Gerig, G., Kikinis, R., Kubler, O., Jolesz, F.A.: Nonlinear anisotropic filtering of MRI data. IEEE Trans. Med. Imaging 11, 221–232 (1992)CrossRefGoogle Scholar
  6. 6.
    Bajla, I., Hollander, I.: Nonlinear filtering of magnetic resonance tomograms by geometry-driven diffusion. Machine Vision and Applications 10, 243–255 (1998)CrossRefGoogle Scholar
  7. 7.
    Ghita, O., Robinson, K., Lynch, M., Whelan, P.F.: MRI diffusion-based filtering: A note on performance characterisation. Comput. Med. Imaging Graph. 29, 267–277 (2005)CrossRefGoogle Scholar
  8. 8.
    Frangakis, A.S., Hegerl, R.: Noise reduction in electron tomographic reconstructions using nonlinear anisotropic diffusion. J. Struct. Biol. 135, 239–250 (2001)CrossRefGoogle Scholar
  9. 9.
    Fernandez, J.J., Li, S.: An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms. J. Struct. Biol. 144, 152–161 (2003)CrossRefGoogle Scholar
  10. 10.
    Fernandez, J.J., Li, S.: Anisotropic nonlinear filtering of cellular structures in cryo-electron tomography. Computing in Science and Engineering 7(5), 54–61 (2005)CrossRefGoogle Scholar
  11. 11.
    Medalia, O., Weber, I., Frangakis, A.S., Nicastro, D., Gerisch, G., Baumeister, W.: Macromolecular architecture in eukaryotic cells visualized by cryoelectron tomography. Science 298, 1209–1213 (2002)CrossRefGoogle Scholar
  12. 12.
    Grunewald, K., Desai, P., Winkler, D.C., Heymann, J.B., Belnap, D.M., Baumeister, W., Steven, A.C.: Three-dimensional structure of herpes simplex virus from cryo-electron tomography. Science 302, 1396–1398 (2003)CrossRefGoogle Scholar
  13. 13.
    Beck, M., Forster, F., Ecke, M., Plitzko, J.M., Melchior, F., Gerisch, G., Baumeister, W., Medalia, O.: Nuclear pore complex structure and dynamics revealed by cryoelectron tomography. Science 306, 1387–1390 (2004)CrossRefGoogle Scholar
  14. 14.
    Cyrklaff, M., Risco, C., Fernandez, J.J., Jimenez, M.V., Esteban, M., Baumeister, W., Carrascosa, J.L.: Cryo-electron tomography of vaccinia virus. Proc. Natl. Acad. Sci. USA 102, 2772–2777 (2005)CrossRefGoogle Scholar
  15. 15.
    Fernandez, J.J., Lawrence, A., Roca, J., Garcia, I., Ellisman, M., Carazo, J.M.: High performance electron tomography of biological specimens. J. Struct. Biol. 138, 6–20 (2002)CrossRefGoogle Scholar
  16. 16.
    Fernandez, J.J., Carazo, J.M., Garcia, I.: Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing. J. Paral. Distr. Computing 64, 285–300 (2004)MATHCrossRefGoogle Scholar
  17. 17.
    Weickert, J., ter Haar Romeny, B.M., Viergever, M.A.: Efficient and reliable schemes for nonlinear diffusion filtering. IEEE Trans. Image Processing 7, 398–410 (1998)CrossRefGoogle Scholar
  18. 18.
    Bruhn, A., Jakob, T., Fischer, M., Kohlberger, T., Weickert, J., Bruning, U., Schnorr, C.: High performance cluster computing with 3D nonlinear diffusion filters. Real-Time Imaging 10, 41–51 (2004)CrossRefGoogle Scholar
  19. 19.
    Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, Cambridge (1992)Google Scholar
  20. 20.
    Barash, D.: A fundamental relationship between bilateral filtering, adaptive smoothing and the nonlinear diffusion equation. IEEE Trans. Patt. Anal. Mach. Intel. 24, 844–847 (2002)CrossRefGoogle Scholar
  21. 21.
    Dunigan, T.H., Vetter, J.S., Worley, P.: Performance evaluation of the SGI Altix 3700. In: Proceedings of the IEEE Intl. Conf. Parallel Processing, ICPP, pp. 231–240 (2005)Google Scholar
  22. 22.
    Akl, S.G.: Superlinear performance in real-time parallel computation. The Journal of Supercomputing 29(1), 89–111 (2004)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • S. Tabik
    • 1
  • E. M. Garzón
    • 1
  • I. García
    • 1
  • J. J. Fernández
    • 1
  1. 1.Dept. Computer Architecture and ElectronicsUniversity of AlmeríaAlmeríaSpain

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